Emmanuel G. Collins

Bio: Emmanuel G. Collins is an academic researcher from Florida State University. The author has contributed to research in topics: Control theory & Linear-quadratic-Gaussian control. The author has an hindex of 26, co-authored 239 publications receiving 3371 citations. Previous affiliations of Emmanuel G. Collins include University College of Engineering & Harris Corporation.

Control Methods of Inverter-Interfaced Distributed Generators in a Microgrid System

Abstract: Microgrids are a new concept for future energy distribution systems that enable renewable energy integration and improved energy management capability. Microgrids consist of multiple distributed generators (DGs) that are usually integrated via power electronic inverters. In order to enhance power quality and power distribution reliability, microgrids need to operate in both grid-connected and island modes. Consequently, microgrids can suffer performance degradation as the operating conditions vary due to abrupt mode changes and variations in bus voltages and system frequency. This paper presents controller design and optimization methods to stably coordinate multiple inverter-interfaced DGs and to robustly control individual interface inverters against voltage and frequency disturbances. Droop-control concepts are used as system-level multiple DG coordination controllers, and control theory is applied to device-level inverter controllers. Optimal control parameters are obtained by particle-swarm-optimization algorithms, and the control performance is verified via simulation studies.

A theory of state covariance assignment for discrete systems

Abstract: In many regulation control problems it is desired to design the controller so that various system states have acceptable root mean squared values. This is a multiple objective problem. One way to satisfy these objectives is to assign a specified state covariance to the system. This paper introduces and solves the following problem: 1) characterize the entire set of state covariances which may be assigned to a linear discrete-time system by state feedback; and 2) find the set of all state feedback gains which will assign an admissible state covariance to the system. Extensions are also presented for state estimate feedback.

Optimal Design and Real-Time Control for Energy Management in Electric Vehicles

Abstract: To extend the lithium-ion (Li-ion) battery cycle life, an active combination of an ultracapacitor (UC) with an energy-dense Li-ion battery is shown as a promising approach for electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). In this paper, the problem of the sizing of the Li-ion battery and UC, as well as the degree of hybridization between the UC power and battery power, is approached from a new perspective, i.e., by solving an optimization problem to minimize fuel consumption. To implement this optimized power sharing in real time, a novel energy management strategy is proposed, which includes battery power reference generation, UC state-of-charge regulation, and forecast control based on the driver commands. Finally, simulations and experiments in which the flywheel + generator + controlled load is used to emulate the vehicle drivetrain are provided to verify the reduced stress on the battery current and the improved fuel economy achieved by the proposed method.

Analysis and Experimental Verification for Dynamic Modeling of A Skid-Steered Wheeled Vehicle

Abstract: Skid-steered vehicles are often used as outdoor mobile robots due to their robust mechanical structure and high maneuverability. Sliding, along with rolling, is inherent to general curvilinear motion, which makes both kinematic and dynamic modeling difficult. For the purpose of motion planning, this paper develops and experimentally verifies dynamic models of a skid-steered wheeled vehicle for general planar (2-D) motion and for linear 3-D motion. These models are characterized by the coefficient of rolling resistance, the coefficient of friction, and the shear deformation modulus, which have terrain-dependent values. The dynamic models also include motor saturation and motor power limitations, which enable correct prediction of vehicle velocities when traversing on hills. It is shown that the closed-loop system that results from inclusion of the dynamics of the [proportional--integral--derivative (PID)] speed controllers for each set of wheels does a much better job than the open-loop model of predicting the vehicle linear and angular velocities. For a vehicle turning with small linear and angular accelerations, the model provides accurate predictions of velocities and reasonable predictions of torques. Hence, the closed-loop model is recommended for motion planning.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Trends in Microgrid Control

Abstract: The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.

Structural control: past, present, and future

Abstract: This tutorial/survey paper: (1) provides a concise point of departure for researchers and practitioners alike wishing to assess the current state of the art in the control and monitoring of civil engineering structures; and (2) provides a link between structural control and other fields of control theory, pointing out both differences and similarities, and points out where future research and application efforts are likely to prove fruitful. The paper consists of the following sections: section 1 is an introduction; section 2 deals with passive energy dissipation; section 3 deals with active control; section 4 deals with hybrid and semiactive control systems; section 5 discusses sensors for structural control; section 6 deals with smart material systems; section 7 deals with health monitoring and damage detection; and section 8 deals with research needs. An extensive list of references is provided in the references section.

Adaptive Control

Abstract: This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.